Improved System Identification Approach Using Wavelet Networks

A new approach is proposed to improve the general identification algor ithm of multidimensional systems using wavelet networks. The general algorithm i nvolves mapping vector input into its norm to avoid problem of dimensionality in construction multidimensional wavelet basis functions. Thus, the basis function s are spherically symmetric without direction selectivity. In order to restore t he direction selectivity, the improved approach weights the input variables befo r e mapping it into a scalar form. The weights can be obtained using universal opt imization algorithms. Generally, only local optimal weights are obtained. Even s o, performance of identification can be improved.